{"title":"季节性情感失调对绿色加密货币的影响","authors":"Zeliha Can Ergun","doi":"10.17261/pressacademia.2023.1773","DOIUrl":null,"url":null,"abstract":"Purpose- Seasonal Affective Disorder (SAD) which arises during the winter when there are fewer daylight hours is a form of the major depressive disease. SAD affects most of the financial markets. Since there is scarce research on the relationship between SAD and cryptocurrency returns, this study is aimed to examine the impact of SAD on green cryptocurrencies. To the best of the author’s knowledge, this is the first study that investigates the relationship between SAD and the returns of green cryptocurrencies, so the study is expected to fill the gap in the related literature. Methodology- Cardano (ADA), Tron (TRX), and Stellar (XLM) are considered for the analysis, which covers the period spanning from January 2018 to March 2023. The multiple regression model has been implemented by including dummies for autumn, Mondays, and tax-loss selling. A specific location must be specified for the latitude information to determine how many hours are spent at night. The latitude of New York City is considered for that calculation because the majority of cryptocurrency users are concentrated in the USA. Findings- The findings demonstrate that the SAD, autumn, Monday, and tax-loss selling effects have no impact on green cryptocurrencies. Due to the worldwide spread of cryptocurrency investors, these effects are probably mitigated. Conclusion- According to the results, arbitrageurs are unable to benefit from generating abnormal returns using seasonal return patterns. Future studies might use non-linear techniques, change the location that is considered when calculating latitude, and include more cryptocurrencies in their examinations. Keywords: Seasonal affective disorder, cryptocurrencies, green finance, behavioral finance, anomalies. JEL Codes: G10, G40, G41","PeriodicalId":15124,"journal":{"name":"Journal of Asian Finance, Economics and Business","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"THE IMPACT OF SEASONAL AFFECTIVE DISORDER ON GREEN CRYPTOCURRENCIES\",\"authors\":\"Zeliha Can Ergun\",\"doi\":\"10.17261/pressacademia.2023.1773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Purpose- Seasonal Affective Disorder (SAD) which arises during the winter when there are fewer daylight hours is a form of the major depressive disease. SAD affects most of the financial markets. Since there is scarce research on the relationship between SAD and cryptocurrency returns, this study is aimed to examine the impact of SAD on green cryptocurrencies. To the best of the author’s knowledge, this is the first study that investigates the relationship between SAD and the returns of green cryptocurrencies, so the study is expected to fill the gap in the related literature. Methodology- Cardano (ADA), Tron (TRX), and Stellar (XLM) are considered for the analysis, which covers the period spanning from January 2018 to March 2023. The multiple regression model has been implemented by including dummies for autumn, Mondays, and tax-loss selling. A specific location must be specified for the latitude information to determine how many hours are spent at night. The latitude of New York City is considered for that calculation because the majority of cryptocurrency users are concentrated in the USA. Findings- The findings demonstrate that the SAD, autumn, Monday, and tax-loss selling effects have no impact on green cryptocurrencies. Due to the worldwide spread of cryptocurrency investors, these effects are probably mitigated. Conclusion- According to the results, arbitrageurs are unable to benefit from generating abnormal returns using seasonal return patterns. Future studies might use non-linear techniques, change the location that is considered when calculating latitude, and include more cryptocurrencies in their examinations. Keywords: Seasonal affective disorder, cryptocurrencies, green finance, behavioral finance, anomalies. 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引用次数: 0
摘要
目的:季节性情绪失调症(SAD)是一种严重的抑郁症,发生在白昼时间较短的冬季。SAD影响了大多数金融市场。由于关于SAD与加密货币回报之间关系的研究很少,因此本研究旨在研究SAD对绿色加密货币的影响。据作者所知,这是第一个调查SAD与绿色加密货币回报之间关系的研究,因此该研究有望填补相关文献的空白。方法-分析考虑了Cardano (ADA), Tron (TRX)和Stellar (XLM),涵盖了2018年1月至2023年3月的时间段。多元回归模型通过包括秋季、周一和税收损失销售的假人来实现。必须为纬度信息指定一个特定的位置,以确定夜间花费多少小时。该计算考虑了纽约市的纬度,因为大多数加密货币用户集中在美国。研究结果表明,SAD、秋季、周一和税收损失抛售效应对绿色加密货币没有影响。由于加密货币投资者遍布全球,这些影响可能会减轻。结论-根据结果,套利者无法从使用季节性回报模式产生的异常回报中获益。未来的研究可能会使用非线性技术,改变计算纬度时考虑的位置,并在他们的研究中包括更多的加密货币。关键词:季节性情感失调,加密货币,绿色金融,行为金融,异常。JEL代码:G10, G40, G41
THE IMPACT OF SEASONAL AFFECTIVE DISORDER ON GREEN CRYPTOCURRENCIES
Purpose- Seasonal Affective Disorder (SAD) which arises during the winter when there are fewer daylight hours is a form of the major depressive disease. SAD affects most of the financial markets. Since there is scarce research on the relationship between SAD and cryptocurrency returns, this study is aimed to examine the impact of SAD on green cryptocurrencies. To the best of the author’s knowledge, this is the first study that investigates the relationship between SAD and the returns of green cryptocurrencies, so the study is expected to fill the gap in the related literature. Methodology- Cardano (ADA), Tron (TRX), and Stellar (XLM) are considered for the analysis, which covers the period spanning from January 2018 to March 2023. The multiple regression model has been implemented by including dummies for autumn, Mondays, and tax-loss selling. A specific location must be specified for the latitude information to determine how many hours are spent at night. The latitude of New York City is considered for that calculation because the majority of cryptocurrency users are concentrated in the USA. Findings- The findings demonstrate that the SAD, autumn, Monday, and tax-loss selling effects have no impact on green cryptocurrencies. Due to the worldwide spread of cryptocurrency investors, these effects are probably mitigated. Conclusion- According to the results, arbitrageurs are unable to benefit from generating abnormal returns using seasonal return patterns. Future studies might use non-linear techniques, change the location that is considered when calculating latitude, and include more cryptocurrencies in their examinations. Keywords: Seasonal affective disorder, cryptocurrencies, green finance, behavioral finance, anomalies. JEL Codes: G10, G40, G41